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Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees

Selection on the Cartesian product is a classic problem in computer science. Recently, an optimal algorithm for selection on A + B, based on soft heaps, was introduced. By combining this approach with layer-ordered heaps (LOHs), an algorithm using a balanced binary tree of A + B selections was propo...

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Detalles Bibliográficos
Autores principales: Kreitzberg, Patrick, Lucke, Kyle, Pennington, Jake, Serang, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093990/
https://www.ncbi.nlm.nih.gov/pubmed/33987456
http://dx.doi.org/10.7717/peerj-cs.483
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author Kreitzberg, Patrick
Lucke, Kyle
Pennington, Jake
Serang, Oliver
author_facet Kreitzberg, Patrick
Lucke, Kyle
Pennington, Jake
Serang, Oliver
author_sort Kreitzberg, Patrick
collection PubMed
description Selection on the Cartesian product is a classic problem in computer science. Recently, an optimal algorithm for selection on A + B, based on soft heaps, was introduced. By combining this approach with layer-ordered heaps (LOHs), an algorithm using a balanced binary tree of A + B selections was proposed to perform selection on X(1) + X(2) + ⋯ + X(m) in o(n⋅m + k⋅m), where X(i) have length n. Here, that o(n⋅m + k⋅m) algorithm is combined with a novel, optimal LOH-based algorithm for selection on A + B (without a soft heap). Performance of algorithms for selection on X(1) + X(2) + ⋯ + X(m) are compared empirically, demonstrating the benefit of the algorithm proposed here.
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spelling pubmed-80939902021-05-12 Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees Kreitzberg, Patrick Lucke, Kyle Pennington, Jake Serang, Oliver PeerJ Comput Sci Algorithms and Analysis of Algorithms Selection on the Cartesian product is a classic problem in computer science. Recently, an optimal algorithm for selection on A + B, based on soft heaps, was introduced. By combining this approach with layer-ordered heaps (LOHs), an algorithm using a balanced binary tree of A + B selections was proposed to perform selection on X(1) + X(2) + ⋯ + X(m) in o(n⋅m + k⋅m), where X(i) have length n. Here, that o(n⋅m + k⋅m) algorithm is combined with a novel, optimal LOH-based algorithm for selection on A + B (without a soft heap). Performance of algorithms for selection on X(1) + X(2) + ⋯ + X(m) are compared empirically, demonstrating the benefit of the algorithm proposed here. PeerJ Inc. 2021-04-28 /pmc/articles/PMC8093990/ /pubmed/33987456 http://dx.doi.org/10.7717/peerj-cs.483 Text en ©2021 Kreitzberg et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Algorithms and Analysis of Algorithms
Kreitzberg, Patrick
Lucke, Kyle
Pennington, Jake
Serang, Oliver
Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees
title Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees
title_full Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees
title_fullStr Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees
title_full_unstemmed Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees
title_short Selection on X(1) + X(2) + ⋯ + X(m) via Cartesian product trees
title_sort selection on x(1) + x(2) + ⋯ + x(m) via cartesian product trees
topic Algorithms and Analysis of Algorithms
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093990/
https://www.ncbi.nlm.nih.gov/pubmed/33987456
http://dx.doi.org/10.7717/peerj-cs.483
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